基于改进蚁群算法的最短路径问题研究及应用

蚁群系统作为一种蚁群算法是解决最短路径问题的一种行之有效的方法.然而,它自身也存在着一些缺陷,主要针对基本蚁群算法易陷入局部最优这一缺陷对其进行改进,集中体现在初始信息素求解和信息素更新这两方面.为了进一步了解改进蚁群算法的优点,进行了实验仿真:将改进的蚁群算法应用子模拟医疗救护GIS中,利用GIS的网络分析功能对城市道路网络的最短路径选择算法进行了深入地探讨研究,并以山西省太原市的交通路线作为实例进行研究.计算机仿真结果表明,改进的蚁群算法在解决最短路径问题时较基本蚁群算法的性能好,它具有一定的理论参考价值和现实意义.

Research and Application for Optimal Routing Problem Based on Improved Ant Colony Algorithm

Ant colony system(ACS),a kind of ant colony algorithm,is a effective way in solving shortest path problem,however,it has some defects.In this paper,ACS is improved for avoiding getting stuck in a local minimum,which mainly reflects in the following two aspects:initial pheromone solution and pheromone updating.In order to further learn the advantages of improved ant colony system(IACS),we run experiments for some times:we will improve the simulation of IACS which is applied to medical care in GIS,using GIS network analysis of urban road network in the shortest path selection algorithm to explore an in-depth research to the road network in Taiyuan,Shanxi as an example.Computer simulation results show that IACS has much better performance in solving shortest path problem than ACS,and it has certain theoretical reference value and practical significance.